Consumers can make emotional buying decisions, but analytics can help businesses better understand, and even predict, seemingly irrational customer behavior.

Reading the Signals

Regardless of what they are purchasing, consumers buy certain products regularly–some planned, and some without conscious forethought. Throughout the consumer journey, customers emit “signals,” offering companies a wealth of traditional data that can be combined with newer big data sources to more accurately inform business and product strategy.

Analytics helps businesses peer into customer behavior and learn to interpret signals. By interpreting data to better understand customer perception and opinion, businesses can overcome their own cognitive and organizational decision bias and influence their customers’ buying behaviors toward what will be, rather than what product managers think should be.

Within the constraints of privacy requirements and end user license agreements, behavioral and transactional data can be fed back into the value chain. This can result in better offers, more targeted products and, ultimately, more willing buyers.

Taking it one step further, using predictive analytics allows businesses to get a clearer picture of what a given customer segment or an individual is likely to do next—embracing the irrationalities and reinforcing the rationalities. Predictive insights surface through an ever-evolving understanding of what triggers create specific outcomes. For example, knowing that certain customers are likely to contribute to charitable causes under certain circumstances may trigger product management leaders to include a social cause with its next offer to that segment.

Achieving Better Outcomes

To capitalize on today’s “irrational” customer attitudes, an organization should move from an assumption-based business culture to a strategy-driven, fact-based culture informed by analytics. Analytics allows businesses to view customer expectations and demands through the lens of behavioral science by reading signals and predicting actions.

Successful organizations can take several key steps to evolve their cultures from traditional to fact-based. These include:

· embedding broad thinking that incorporates new and more efficient ways to conduct business using analytics;

· integrating technology components such as scoring engines, signal processors, enterprise rules engines and learning engines that make analytic outputs available to critical business processes in real or near-real time;

· incorporating organizational change-management practices to guide the restructuring, education and training that can make analytics stick long-term; and

· monitoring performance using a fact-based business intelligence platform that enables companies to tune business and technical processes to improve road map components.

By embedding analytics and moving toward a fact-based culture, businesses can gain a more accurate view of what makes customers tick and ultimately achieve better business outcomes. As we’ve established, customers don't act rationally all the time— or even most of the time. So, although the factors that motivate behavior don’t always make sense, businesses can use customer data to rationalize the irrational customer.

John Lucker (@johnlucker) is a principal and the global advanced analytics and modeling market offering leader at Deloitte Consulting LLP. He is also a U.S. leader in Deloitte Touche Tohmatsu Limited’s Deloitte Analytics Institute.

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